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dc.contributor.authorAlfeo, Antonio Luca
dc.contributor.authorCastelló Ferrer, Eduardo
dc.contributor.authorLizarribar Carrillo, Yago
dc.contributor.authorGrignard, Arnaud
dc.contributor.authorAlonso Pastor, Luis
dc.contributor.authorSleeper, Dylan T.
dc.contributor.authorCimino, Mario G.C.A.
dc.contributor.authorLepri, Bruno
dc.contributor.authorVaglini, Gigliola
dc.contributor.authorLarson, Kent
dc.contributor.authorDorigo, Marco
dc.contributor.authorPentland, Alex ('Sandy')
dc.date.accessioned2019-03-01T07:08:24Z
dc.date.available2019-03-01T07:08:24Z
dc.date.issued2018-10-18
dc.identifier.urihttp://hdl.handle.net/1721.1/120583
dc.description.abstractModern cities are growing ecosystems that face new challenges due to the increasing population demands. One of the many problems they face nowadays is waste management, which has become a pressing issue requiring new solutions. Swarm robotics systems have been attracting an increasing amount of attention in the past years and they are expected to become one of the main driving factors for innovation in the field of robotics. The research presented in this paper explores the feasibility of a swarm robotics system in an urban environment. By using bio-inspired foraging methods such as multi-place foraging and stigmergy-based navigation, a swarm of robots is able to improve the efficiency and autonomy of the urban waste management system in a realistic scenario. To achieve this, a diverse set of simulation experiments was conducted using real-world GIS data and implementing different garbage collection scenarios driven by robot swarms. Results presented in this research show that the proposed system outperforms current approaches. Moreover, results not only show the efficiency of our solution, but also give insights about how to design and customize these systems.en_US
dc.language.isoen_USen_US
dc.publisherArXiven_US
dc.rightsAttribution-NonCommercial 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/us/*
dc.subjectRoboticsen_US
dc.subjectSmart Citiesen_US
dc.subjectSwarm Intelligenceen_US
dc.subjectAutonomous Citiesen_US
dc.subjectDistributed Systemsen_US
dc.titleUrban Swarms: A new approach for autonomous waste managementen_US
dc.typeArticleen_US
dc.identifier.citationarXiv:1810.07910en_US


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